Gregory Kuhlmann

The University of Texas at Austin

Papers

3

Total Citations

89

H-Index

3

About

Gregory Kuhlmann is a leading researcher in autonomous robotics, with a career distinguished by advancing the capabilities of mobile robots to perceive, localize, and make decisions in complex, real-world environments. His foundational work on "Practical Vision-Based Monte Carlo Localization on a Legged Robot" (57 citations) pioneered the use of visual data for global positioning on dynamic platforms like legged robots, moving beyond traditional wheeled robots and range-finding sensors. This research tackled the critical challenge of uncertainty in robot perception, a theme he further explored in his study "From pixels to multi-robot decision-making: A study in uncertainty" (21 citations). Kuhlmann’s impact extends to extreme environments, where he contributed to the ENDURANCE AUV project, enabling autonomous scientific exploration of ice-covered Antarctic lakes (11 citations). His work demonstrates a rare ability to bridge low-level sensor processing with high-level multi-robot decision-making, making him a notable figure in field robotics and autonomous systems.

Research Focus

Key Achievements

3
H-Index
3
Papers
89
Total Citations
30
Avg Citations/Paper
🏆 Most Cited Paper
Practical Vision-Based Monte Carlo Localization on a Legged Robot
57 citations · 2006
📈 Most Prolific Year: 2006 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: The University of Texas at Austin

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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